Teaching philosophy

This course introduces the key concepts of machine learning with an emphasis on intuition first. Then, the mathematical foundations are presented via practical exercises, allowing you to truly get a ‘feel’ for the equations. Finally, hands-on coding exercises translate the math into working algorithms. By the end of the course, the main ML algorithms will hold no secrets for you!

Examples and tutorials are drawn from particle physics, though no background is required. It’s a bit of self-promotion 😉 but also a deliberate choice. Some of you might fall in love with the subatomic world and want to explore further (an awesome journey, I promise). Even if quarks and bosons aren’t your thing, you’ll build a valuable skill: learning how to enter an unfamiliar technical field and extract the essential information relevant to solve your beautiful ML problem.